Typically, customer service representatives (CSRs) in environments such as call centers have a computer workstation that acts as a hub for a multitude of software applications (e.g., telephony, email, knowledge base, customer relationship management, sales/order processing, marketing, inventory management, and so forth) that enable the agent to effectively respond to digital communications from a customer base. When a customer initiates a communication session with the CSR at the call center (for example, a voice call or video call call), the CSR may execute a variety of software applications on his or her workstation during the communication session to respond to the caller's questions. Typically, the CSR conducts a verbal conversation with the caller to understand the reason for the call and to provide associated information to the caller. In cases when a caller is reaching out to the CSR with a sensitive inquiry or problem, the level of empathy displayed by the CSR is crucial to improving the customer experience and producing a positive resolution to the situation.
However, it is very difficult for CSRs to understand whether they are acting in a manner that exhibits empathy and to improve their behavior to provide more empathetic communications with the callers. Generally, this type of study and improvement is only the result of many years of experience, and there is no reliable, accurate computerized methodology to automatically analyze a CSR's behavior during a communication session to determine a confidence level in the CSR's empathy and to provide real-time feedback and suggestions to the CSR in ways that they could improve their behavior. Generally, existing computing systems are equipped to only analyze